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Riparian forests are known as hot spots of nitrogen cycling in landscapes. Climate warming speeds up the cycle. Here we present results from a multi-annual high temporal-frequency study of soil, stem, and ecosystem (eddy covariance) fluxes of N2O from a typical riparian forest in Europe. Hot moments (extreme events of N2O emission) lasted a quarter of the study period but contributed more than half of soil fluxes. We demonstrate that high soil emissions of N2O do not escape the ecosystem but are processed in the canopy. Rapid water content change across intermediate soil moisture was a major determinant of elevated soil emissions in spring. The freeze-thaw period is another hot moment. However, according to the eddy covariance measurements, the riparian forest is a modest source of N2O. We propose photochemical reactions and dissolution in canopy-space water as reduction mechanisms.

Crop residue incorporation is a common practice to increase or restore organic matter stocks in agricultural soils. However, this practice often increases emissions of the powerful greenhouse gas nitrous oxide (N2O). Previous meta-analyses have linked various biochemical properties of crop residues to N2O emissions, but the relationships between these properties have been overlooked, hampering our ability to predict N2O emissions from specific residues. Here we combine comprehensive databases for N2O emissions from crop residues and crop residue biochemical characteristics with a random-meta-forest approach, to develop a predictive framework of crop residue effects on N2O emissions. On average, crop residue incorporation increased soil N2O emissions by 43% compared to residue removal, however crop residues led to both increases and reductions in N2O emissions. Crop residue effects on N2O emissions were best predicted by easily degradable fractions (i.e. water soluble carbon, soluble Van Soest fraction (NDS)), structural fractions and N returned with crop residues. The relationship between these biochemical properties and N2O emissions differed widely in terms of form and direction. However, due to the strong correlations among these properties, we were able to develop a simplified classification for crop residues based on the stage of physiological maturity of the plant at which the residue was generated. This maturity criteria provided the most robust and yet simple approach to categorize crop residues according to their potential to regulate N2O emissions. Immature residues (high water soluble carbon, soluble NDS and total N concentration, low relative cellulose, hemicellulose, lignin fractions, and low C:N ratio) strongly stimulated N2O emissions, whereas mature residues with opposite characteristics had marginal effects on N2O. The most important crop types belonging to the immature residue group – cover crops, grasslands and vegetables – are important for the delivery of multiple ecosystem services. Thus, these residues should be managed properly to avoid their potentially high N2O emissions.

Studies that quantify plant methane (CH4) emission rely on the accurate measurement of small changes in the mixing ratio of CH4 that coincide with much larger changes in the mixing ratio of volatile organic compounds (VOCs). Here, we assessed whether 11 commonly occurring VOCs (e.g. methanol, α- and β-pinene, Δ3-carene) interfered with the quantitation of CH4 by five laser-absorption spectroscopy and Fourier-transformed infrared spectroscopy (FTIR) based CH4 analysers, and quantified the interference of seven compounds on three instruments. Our results showed minimal interference with laser-based analysers and underlined the importance of identifying and compensating for interferences with FTIR instruments. When VOCs were not included in the spectral library, they exerted a strong bias on FTIR-based instruments (64–1800 ppbv apparent CH4 ppmv−1 VOC). Minor (0.7–126 ppbv ppmv−1) interference with FTIR-based measurements were also detected when the spectrum of the interfering VOC was included in the library. In contrast, we detected only minor ( ppbv ppmv−1) and transient (< 1 min) VOC interferences on laser-absorption spectroscopy-based analysers. Overall, our results demonstrate that VOC interferences have only minor effects on CH4 flux measurements in soil chambers, but may severely impact stem and shoot flux measurements. Laser-absorption-based instruments are better suited for quantifying CH4 fluxes from plant leaves and stems than FTIR-based instruments; however, significant interferences in shoot chamber measurements could not be excluded for any of the tested instruments. Our results furthermore showed that FTIR can precisely quantify VOC mixing ratios and could therefore provide a method complementary to proton-transfer-reaction mass spectrometry (PTR-MS).

This study assessed how digestate and the liquid fraction (LF) of digestate would perform as candidate RENURE fertilisers (recovered nitrogen from manure) in nitrate vulnerable zones under the proposed criteria of the Joint Research Centre, namely, (i) a mineral nitrogen to total nitrogen ratio ≥ 90% (Nmin:TN ≥ 90%) or a total organic carbon to TN ratio ≤ 3 (TOC:TN ≤ 3), (ii) limits of ≤300 copper (Cu) mg kg−1 and ≤800 Zinc (Zn) mg kg−1. These criteria were applied to unpublished data (n = 2622) on digestate compositional properties, further amended with data from the literature (n = 180), digestate analysis from seven full-scale biogas facilities (n = 14), and biogas industry stakeholders (n = 23). The results showed that Cu and Zn mostly met the criteria, with compliance rates of 94.7% (of 1035 entries) and 95.0% (of 1038 entries), respectively. Just above 5% (of 1856 entries) met the Nmin/TN ≥ 90% criterion, while 36% (of 1583 entries) met the TOC/TN ≤ 3 criterion, while total compliance was 32% (of 1893 entries). When targeting the LF, total compliance increased noticeably, between 43 and 58% depending on DM range, indicating that LFs are better suited RENURE candidate fertilisers than unseparated digestate.

Nitrification inhibitors have often been found to reduce nitrous oxide (N2O) emissions from agricultural soils, but N2O mitigation is variable and may depend on soil and climate variables. This study investigated how key abiotic factors modified the effect of Vizura (R), a new formulation with the nitrification inhibitor 3,4-dimethylpyrazole phosphate (DMPP) for livestock slurry, on N2O emissions. Two different incubations were carried out to investigate the main and interactive effects of selected factors on N2O emissions after manure application to soil. Experiment 1 studied two contrasting soil textures (coarse sandy vs sandy loam soil) and temperatures (10 vs 20 degrees C); Experiment 2 used the coarse sandy soil to compare two levels of soil pH (4.9 vs 6.4) and nitrate availability (0 vs 50 mg N kg(-1)). Nitrous oxide emissions and spatial distribution of mineral N were determined in both experiments, while temporal dynamics of mineral N pools and N-cycling microbial communities were investigated in Experiment 2 only. In sandy loam soil, the efficiency of DMPP to mitigate N2O emissions after manure application was similar at 10 and 20 degrees C, while in the coarse sandy soil DMPP was not effective at 10 degrees C, possibly because of low nitrification activity. Nitrous oxide emissions from the coarse sandy soil were higher at pH 4.9 than at pH 6.4, which was accompanied by lower abundance of nosZ genes and therefore potentially higher N2O/ (N-2+N2O) product ratios. DMPP significantly reduced the abundance of ammonia-oxidizing bacteria (AOB) on all sampling days, but had no effect on ammonia-oxidizing archaea (AOA). The inhibitor also reduced the abundance of comammox, which are newly discovered complete ammonia oxidizers. This study showed how soil conditions (soil texture, temperature, pH), through effects on nitrifiers and denitrifiers, and mineral N distribution, can modify the efficiency of nitrification inhibitors in reducing N2O emissions from livestock slurry.

Primary tropical forests generally exhibit large gaseous nitrogen (N) losses, occurring as nitric oxide (NO), nitrous oxide (N2O) or elemental nitrogen (N2). The release of N2O is of particular concern due to its high global warming potential and destruction of stratospheric ozone. Tropical forest soils are predicted to be among the largest natural sources of N2O; however, despite being the world’s second-largest rainforest, measurements of gaseous N-losses from forest soils of the Congo Basin are scarce. In addition, long-term studies investigating N2O fluxes from different forest ecosystem types (lowland and montane forests) are scarce. In this study we show that fluxes measured in the Congo Basin were lower than fluxes measured in the Neotropics, and in the tropical forests of Australia and South East Asia. In addition, we show that despite different climatic conditions, average annual N2O fluxes in the Congo Basin’s lowland forests (0.97 ± 0.53 kg N ha−1 year−1) were comparable to those in its montane forest (0.88 ± 0.97 kg N ha−1 year−1). Measurements of soil pore air N2O isotope data at multiple depths suggests that a microbial reduction of N2O to N2 within the soil may account for the observed low surface N2O fluxes and low soil pore N2O concentrations. The potential for microbial reduction is corroborated by a significant abundance and expression of the gene nosZ in soil samples from both study sites. Although isotopic and functional gene analyses indicate an enzymatic potential for complete denitrification, combined gaseous N-losses (N2O, N2) are unlikely to account for the missing N-sink in these forests. Other N-losses such as NO, N2 via Feammox or hydrological particulate organic nitrogen export could play an important role in soils of the Congo Basin and should be the focus of future research., The ISME Journal, 15, ISSN:1751-7362, ISSN:1751-7370

Currently, nitrogen fertilizers are utilized to meet 48% of the total global food demand. The demand for nitrogen fertilizers is expected to grow as global populations continue to rise. The use of nitrogen fertilizers is associated with many negative environmental impacts and is a key source of greenhouse and harmful gas emissions. In recent years, urease and nitrification inhibitors have emerged as mitigation tools that are presently utilized in agriculture to prevent nitrogen losses and reduce greenhouse and harmful gas emissions that are associated with the use of nitrogen-based fertilizers. Both classes of inhibitor work by different mechanisms and have different physiochemical properties. Consequently, each class must be evaluated on its own merits. Although there are many benefits associated with the use of these inhibitors, little is known about their potential to enter the food chain, an event that may pose challenges to food safety. This phenomenon was highlighted when the nitrification inhibitor dicyandiamide was found as a residual contaminant in milk products in 2013. This comprehensive review aims to discuss the uses of inhibitor technologies in agriculture and their possible impacts on dairy product safety and quality, highlighting areas of concern with regards to the introduction of these inhibitor technologies into the dairy supply chain. Furthermore, this review discusses the benefits and challenges of inhibitor usage with a focus on EU regulations, as well as associated health concerns, chemical behavior, and analytical detection methods for these compounds within milk and environmental matrices.

Aims Decomposition of manure deposited onto pasture from grazing animals represents an important process for carbon (C) and nitrogen (N) cycles in grassland systems. However, studies investigating manure decomposition are scarce; especially in sub-Saharan Africa (SSA). Methods In this study, we measured decomposition of three types of animal manure (cattle, sheep, goat) over >1 year using litter bags at four climatically different sites across Kenya. Results Manure dry matter, total C, total N and ammonium concentrations decreased exponentially, with the most rapid decrease occurring during the first few weeks following application, followed by slower changes during the following 2–3 months. Rates of N mineralization were lower than those for C mineralization, resulting in decreasing C/N ratios over time. Generally, cattle manure decomposed faster than sheep or goat manure despite having a higher initial C/N ratio and lower N concentration, with decomposition rates for dry matter ranging from 0.200 to 0.989 k year−1. Cellulose decomposed first, while lignin concentrations increased among all manure types and at all sites. Conclusions We found that total manure decomposition rates were positively correlated with cumulative precipitation and aridity index, but negatively correlated with mean temperature. Our results show much slower decomposition rates of manures in semi-arid tropical environments of East Africa as compared to the few previous studies in temperate climates.

Wildfires strongly regulate carbon (C) cycling and storage in boreal forests and account for almost 10% of global fire C emissions. However, the anticipated effects of climate change on fire regimes may destabilize current C-climate feedbacks and switch the systems to new stability domains. Since most of these forests are located in upland soils where permafrost is widespread, the expected climate warming and drying combined with more active fires may alter the greenhouse gas (GHG) budgets of boreal forests and trigger unprecedented changes in the global C balance. Therefore, a better understanding of the effects of fires on the various spatial and temporal patterns of GHG fluxes of different physical environments (permafrost and nonpermafrost soils) is fundamental to an understanding of the role played by fire in future climate feedbacks. While large amounts of C are released during fires, postfire GHG fluxes play an important role in boreal C budgets over the short and long term. The timescale over which the vegetation cover regenerates seems to drive the recovery of C emissions after both low- and high-severity fires, regardless of fire-induced changes in soil decomposition. In soils underlain by permafrost, fires increase the active layer depth for several years, which may alter the soil dynamics regulating soil GHG exchange. In a scenario of global warming, prolonged exposition of previously immobilized C could result in higher carbon dioxide emission during the early fire succession. However, without knowledge of the contribution of each respiration component combined with assessment of the warming and drying effects on both labile and recalcitrant soil organic matter throughout the soil profile, we cannot advance on the most relevant feedbacks involving fire and permafrost. Fires seem to have either negligible effects on methane (CH4) fluxes or a slight increase in CH4 uptake. However, permafrost thawing driven by climate or fire could turn upland boreal soils into temporary CH4 sources, depending on how fast the transition from moist to drier soils occurs. Most studies indicate a slight decrease or no significant change in postfire nitrous oxide (N2O) fluxes. However, simulations have shown that the temperature sensitivity of denitrification exceeds that of soil respiration; thus, the effects of warming on soil N2O emissions may be greater than on C emissions.

To accurately assess the roles of agriculture in securing food security and maintaining environmental sustainability, it is essential to improve the representation of crop growth, development, and yield formation in global land models that traditionally focus on energy, water, carbon, and nitrogen exchanges between land and the atmosphere. In this study, a process‐based agricultural module has been coupled with the Dynamic Land Ecosystem Model (DLEM‐AG2.0) for assessing how multiple environmental factors (climate change, atmospheric CO2 concentration, tropospheric O3, and nitrogen deposition) and human activities (land use/cover change, nitrogen fertilizer use, and irrigation) have affected the crop growth, development, yield, carbon (C), nitrogen (N), and water cycles in agroecosystems. Here we describe the model structure for simulating crop growth, development, and yield formation in the DLEM‐AG2.0, and then we validate the model using field observations and a national yield survey for three major crops (wheat, maize, and rice) in China during 1980–2012. Results show that the DLEM‐AG2.0 is capable of simulating the dynamic processes of phenological development, leaf growth expansion, biomass accumulation, biomass allocation, and yield formation for wheat, maize, and rice with normalized root mean square errors of the simulations of less than 20%. Our model‐based yield estimation for the three major crops at the national scale for the period 1980–2012 is generally consistent with the national yield survey in China. The crop representation in the DLEM‐AG2.0 is flexible for extrapolating to a global scale after rigorous testing with both site‐specific and regional observations. Further advancement of agricultural modeling within the global land modeling framework will require consideration of human perception and behavior for adapting and mitigating global change.

We measured methane (CH4) exchange rates with automatic chambers at the forest floor of a nutrient-rich drained peatland in 2011–2013. The fen, located in southern Finland, was drained for forestry in 1969 and the tree stand is now a mixture of Scots pine, Norway spruce, and pubescent birch. Our measurement system consisted of six transparent chambers and stainless steel frames, positioned on a number of different field and moss layer compositions. Gas concentrations were measured with an online cavity ring-down spectroscopy gas analyzer. Fluxes were calculated with both linear and exponential regression. The use of linear regression resulted in systematically smaller CH4 fluxes by 10–45 % as compared to exponential regression. However, the use of exponential regression with small fluxes ( 4 m−2 h−1) typically resulted in anomalously large absolute fluxes and high hour-to-hour deviations. Therefore, we recommend that fluxes are initially calculated with linear regression to determine the threshold for low fluxes and that higher fluxes are then recalculated using exponential regression. The exponential flux was clearly affected by the length of the fitting period when this period was 4 flux: the forest floor acted as a CH4 sink particularly from early summer until the end of the year, while in late winter the flux was very small and fluctuated around zero. However, the magnitude of fluxes was relatively small throughout the year, ranging mainly from −130 to +100 µg CH4 m−2 h−1. CH4 emission peaks were observed occasionally, mostly in summer during heavy rainfall events. Diurnal variation, showing a lower CH4 uptake rate during the daytime, was observed in all of the chambers, mainly in the summer and late spring, particularly in dry conditions. It was attributed more to changes in wind speed than air or soil temperature, which suggest that physical rather than biological phenomena are responsible for the observed variation. The annual net CH4 exchange varied from −104 ± 30 to −505 ± 39 mg CH4 m−2 yr−1 among the six chambers, with an average of −219 mg CH4 m−2 yr−1 over the 2-year measurement period.

Chemical composition of root and shoot litter controls decomposition and, subsequently, C availability for biological nitrogen transformation processes in soils. While aboveground plant residues have been proven to increase N2O emissions, studies on root litter effects are scarce. This study aimed (1) to evaluate how fresh maize root litter affects N2O emissions compared to fresh maize shoot litter, (2) to assess whether N2O emissions are related to the interaction of C and N mineralization from soil and litter, and (3) to analyze changes in soil microbial community structures related to litter input and N2O emissions. To obtain root and shoot litter, maize plants (Zea mays L.) were cultivated with two N fertilizer levels in a greenhouse and harvested. A two-factorial 22 d laboratory incubation experiment was set up with soil from both N levels (N1, N2) and three litter addition treatments (control, root, root + shoot). We measured CO2 and N2O fluxes, analyzed soil mineral N and water-extractable organic C (WEOC) concentrations, and determined quality parameters of maize litter. Bacterial community structures were analyzed using 16S rRNA gene sequencing. Maize litter quality controlled NO3- and WEOC availability and decomposition-related CO2 emissions. Emissions induced by maize root litter remained low, while high bioavailability of maize shoot litter strongly increased CO2 and N2O emissions when both root and shoot litter were added. We identified a strong positive correlation between cumulative CO2 and N2O emissions, supporting our hypothesis that litter quality affects denitrification by creating plant-litter-associated anaerobic microsites. The interdependency of C and N availability was validated by analyses of regression. Moreover, there was a strong positive interaction between soil NO3- and WEOC concentration resulting in much higher N2O emissions, when both NO3- and WEOC were available. A significant correlation was observed between total CO2 and N2O emissions, the soil bacterial community composition, and the litter level, showing a clear separation of root + shoot samples of all remaining samples. Bacterial diversity decreased with higher N level and higher input of easily available C. Altogether, changes in bacterial community structure reflected degradability of maize litter with easily degradable C from maize shoot litter favoring fast-growing C-cycling and N-reducing bacteria of the phyla Actinobacteria, Chloroflexi, Firmicutes, and Proteobacteria. In conclusion, litter quality is a major driver of N2O and CO2 emissions from crop residues, especially when soil mineral N is limited.

Agricultural sustainability is compromised by nitrogen (N) losses caused by soil microbial activity. Nitrous oxide (N2O) is a potent greenhouse gas (GHG) produced as consequence of nitrification and denitrification processes in soils. Nitrification inhibitors (NI) as 3,4-dimethylpyrazole-succinic acid (DMPSA) are useful tools to reduce these N losses from fertilization. The objective of this work was to test the efficiency of DMPSA in two different tillage management systems, conventional tillage (CT) and no-tillage (NT), in a winter wheat crop under Humid Mediterranean conditions. N fertilizer was applied as ammonium sulphate (AS) with or without DMPSA in a single or split application, including an unfertilized treatment. GHG fluxes N2O, CO2 and CH4) were measured by the closed chamber method. amoA and nosZl genes were quantified by qPCR as indicators of nitrifying and denitrifying populations. Nitrification was inhibited by DMPSA in both CT and NT, while the higher water filled pore space (WFPS) in NT promoted a better efficiency of DMPSA in this system. This higher efficiency might be due to a greater N2O reduction to N-2 as result of the nosZl gene induction. Consequently, DMPSA was able to reduce N2O emissions down to the unfertilized levels in NT. Provided that NT reduced CO2 emissions and maintained crop yield compared to CT, the application DMPSA under NT management is a promising strategy to increase agro-systems sustainability under Humid Mediterranean conditions. (C) 2019 The Author(s). Published by Elsevier B.V. This project was funded by de Spanish Government (AGL2015-64582-C3-2-R MINECO/FEDER and RTI2018-094623-B-C21 MCIU/AEI/FEDER, UE), by the Basque Government (IT-932-16) and by EuroChem Agro Iberia S.L.-UPV/EHU 2017.0016. Mario Corrochano-Monsalve held a grant from the Ministry of Economy and Business of the Spanish Government and Ximena Huerfano received a specialization fellowship for PhD researches from the UPV/EHU.

Ground-based atmospheric observations of CO2, δ(O2∕N2), N2O, and CH4 were used to make estimates of the air–sea fluxes of these species from the Lüderitz and Walvis Bay upwelling cells in the northern Benguela region, during upwelling events. Average flux densities (±1σ) were 0.65±0.4 µmol m−2 s−1 for CO2, -5.1±2.5 µmol m−2 s−1 for O2 (as APO), 0.61±0.5 nmol m−2 s−1 for N2O, and 4.8±6.3 nmol m−2 s−1 for CH4. A comparison of our top-down (i.e., inferred from atmospheric anomalies) flux estimates with shipboard-based measurements showed that the two approaches agreed within ±55 % on average, though the degree of agreement varied by species and was best for CO2. Since the top-down method overestimated the flux density relative to the shipboard-based approach for all species, we also present flux density estimates that have been tuned to best match the shipboard fluxes. During the study, upwelling events were sources of CO2, N2O, and CH4 to the atmosphere. N2O fluxes were fairly low, in accordance with previous work suggesting that the evasion of this gas from the Benguela is smaller than for other eastern boundary upwelling systems (EBUS). Conversely, CH4 release was quite high for the marine environment, a result that supports studies that indicated a large sedimentary source of CH4 in the Walvis Bay area. These results demonstrate the suitability of atmospheric time series for characterizing the temporal variability of upwelling events and their influence on the overall marine greenhouse gas (GHG) emissions from the northern Benguela region.

© 2016, Springer Science+Business Media Dordrecht. Enteric methane (CH4) generated in the gastrointestinal tract of ruminant represents the source of the greatest direct greenhouse gas (GHG) released from the livestock sector. We evaluated the global potential reduction of enteric CH4emissions released from dairy cattle through amendment of their traditional diets in 183 countries aggregated to 11 regions. Amending dairy cattle diets involves increasing the concentration of lipid (up to 6 %) and decreasing the concentration of fiber, without affecting the total gross energy intake (GEI). Enteric CH4emissions were calculated by using a mathematical model developed to include dietary intervention. In 2012, we found a global potential reduction of 15.7 % of enteric CH4 emissions from dairy cattle. The highest potential reduction per unit of milk produced occurs in Africa followed by South America and Asia (55, 46 and 34 %, respectively). The amended diets proposed here, mostly affect the regions in which demand for animal source protein will be greatest in the future. Because lipid supplementation may result in an indirect effect on CH4and nitrous oxide (N2O) emissions from manure management, they were also estimated. Methane emissions from manure management would decrease by 13 %, while N2O emissions would increase by 21 % due to diet amendment. On balance, the total potential reduction of GHG emissions through diet amendment was 104 MtCO2eq annually. Moreover, amending diets would increase global milk production by 13 %. This study evaluated a global potential reduction of GHG emissions directly released from dairy cattle, however, future advancements dealing with the analysis of the upstream emissions associated to these diet changes are needed.

This study aims to develop a deep-learning-based and plant data-driven framework for process modeling to help understanding plant-wide processes. The systematic framework consists of the following steps: data processing based on domain-knowledge, deep-learning model development, model selection using information criteria, and global sensitivity analysis with Monte-Carlo simulations. The assessment of the quality of the optimal deep-learning model to support plant-wide process understanding is the key emphasis of this framework. The proposed framework was applied for analyzing long-term data from wastewater treatment plants to predict nitrous oxide emission characteristics. The results showed a promising potential of the framework to systematically and efficiently develop fit-for-purpose deep-learning models with highly favorable cross-validation statistics (R2). The framework is expected to facilitate the development of versatile deep-learning models based on plant data encompassing nonlinear and complex process phenomena, where especially mechanistic models are not available.

Among strategies suggested to decrease agricultural soil N2O losses, the use of nitrification inhibitors such as DMPP (3,4-dimethylpyrazole phosphate) has been proposed. However, the efficiency of DMPP might be affected by soil amendments, such as biochar, which has been shown to reduce N2O emissions. This study evaluated the synergic effect of a woody biochar applied with DMPP on soil N2O emissions. A incubation study was conducted with a silt loam soil and a biochar obtained from Pinus taeda at 500 degrees C. Two biochar rates (0 and 2% (w/w)) and three different nitrogen treatments (unfertilized, fertilized and fertilized + DMPP) were assayed under two contrasting soil water content levels (40% and 80% of water filled pore space (WFPS)) over a 163 day incubation period. Results showed that DMPP reduced N2O emissions by reducing ammonia-oxidizing bacteria (AOB) populations and promoting the last step of denitrification (measured by the ratio nosZI + nosZII/nirS + nirK genes). Biochar mitigated N2O emissions only at 40% WFPS due to a reduction in AOB population. However, when DMPP was applied to the biochar amended soil, a counteracting effect was observed, since the N2O mitigation induced by DMPP was lower than in control soil, demonstrating that this biochar diminishes the efficiency of the DMPP both at low and high soil water contents. This work was funded by the Spanish Government (AGL2015-64582-C3-2-R MINECO/FEDER), by the Basque Government (IT-932-16) and by the European Union (FACCE-CSA no 276610/MIT04-DESIGN-UPVASC, FACCE-CSA no 2814ERA01A and 2814ERA02A). This work is also supported by the USDA/NIFA Interagency Climate Change Grant Proposal number 2014-02114 [Project number 6657-12130-002-08I, Accession number 1003011] under the Multi-Partner Call on Agricultural Greenhouse Gas Research of the FACCE-Joint Program Initiative. Any opinions, findings, or recommendation expressed in this publication are those of the authors and do not necessarily reflect the view of the USDA. MLC was supported by a Ramon y Cajal contract from the Spanish Ministry of Economy and Competitiveness and thanks Fundacion Seneca for financing the project 19281/PI/14.

Feedstocks from lignocellulosic biomass (LCB) include crop residues and dedicated perennial biomass crops. The latter are often considered superior in terms of climate change mitigation potential. Uncertainty remains over their availability as feedstocks for biomass provision and the net greenhouse gas emissions (GHG) during crop production. Our objective was to assess the optimal land allocation to wheat and Miscanthus in a specific case study located in England, to increase biomass availability, improve the carbon balance (and reduce the consequent GHG emissions), and minimally constrain grain production losses from wheat. Using soil and climate variables for a catchment in east England, biomass yields and direct nitrogen emissions were simulated with validated process‐based models. A ‘Field to up‐stream factory gate’ life‐cycle assessment was conducted to estimate indirect management‐related GHG emissions. Results show that feedstock supply from wheat straw can be supplemented beneficially with LCB from Miscanthus grown on selected low‐quality soils. In our study, 8% of the less productive arable land area was dedicated to Miscanthus, increasing total LCB provision by about 150%, with a 52% reduction in GHG emission per ton LCB delivered and only a minor effect on wheat grain production (−3%). In conclusion, even without considering the likely carbon sequestration in impoverished soils, agriculture should embrace the opportunities to provide the bioeconomy with LCB from dedicated, perennial crops. © 2019 Society of Chemical Industry and John Wiley & Sons, Ltd

Organic agriculture depends on recycling of N to sustain crop production, and the use of catch crops to prevent leaching losses during winter is part of this strategy. The finding in this study, that catch crop residues were a more consistent source of nitrous oxide emissions in spring than synthetic fertiliser, indicates catch crop residue decomposition may contribute negatively to the climate impact of the farming system. Management practices are needed that reduce the potential for denitrification, which is the main source of nitrous oxide. Possible strategies include cultivation to promote aerobic rather than anaerobic degradation, and timing of manure application to avoid that mineral N from manure accumulates during residue decomposition. Agricultural soils are a significant source of anthropogenic nitrous oxide (N2O) emissions, because of fertilizer application and decomposition of crop residues. We studied interactions between nitrogen (N) amendments and soil conditions in a 2-year field experiment with or without catch crop incorporation before seeding of spring barley, and with or without application of N in the form of digested liquid manure or mineral N fertilizer. Weather conditions, soil inorganic N dynamics, and N2O emissions were monitored during spring, and soil samples were analyzed for abundances of nitrite reduction (nirK and nirS) and N2O reduction genes (nosZ clade I and II), and structure of nitrite- and N2O-reducing communities. Fertilization significantly enhanced soil mineral N accumulation compared to treatments with catch crop residues as the only N source. Nitrous oxide emissions, in contrast, were stimulated in rotations with catch crop residue incorporation, probably as a result of concurrent net N mineralization, and O2 depletion associated with residue degradation in organic hotspots. Emissions of N2O from digested manure were low in both years, while emissions from mineral N fertilizer were nearly absent in the first year, but comparable to emissions from catch crop residues in the second year with higher precipitation and delayed plant N uptake. Higher gene abundances, as well as shifts in community structure, were also observed in the second year, which were significantly correlated to NO− 3 availability. Both the size and structure of the nitrite- and N2O-reducing communities correlated to the difference in N2O emissions between years, while there were no consistent effects of management as represented by catch crops or fertilization. It is concluded that N2O emissions were constrained by environmental, rather than the genetic potential for nitrite and N2O reduction.

Nitrous oxide (N2O) emissions are highly variable in time, with high peak emissions lasting a few days to several weeks and low background emissions. This temporal variability is poorly understood which hampers the simulation of daily N2O emissions. In structured soils, like clay and peat, aggregates hamper the diffusion of oxygen, which leads to anaerobic microsites in the soil, favourable for denitrification. Diffusion of N2O out of the aggregates is also hampered, which leads to delayed emissions and increased reduction of N2O to N2. In this model simulation study we investigate the effect of aggregates in soils on the N2O emissions. We present a parameterization to simulate the effects of aggregates on N2O production by denitrification and on N2O reduction. The parameterization is based on the mobile-immobile model concept. It was implemented in a field-scale hydrological-biogeochemical model combination. We compared the simulated fluxes with observed fluxes from a fertilized and drained peat soil under grass. The results of this study show that aggregates strongly affect the simulated N2O emissions: peak emissions are lower, whereas the background emissions are slightly higher. Including the effect of aggregates caused a 40% decrease in the simulated annual emissions relative to the simulations without accounting for the effects of aggregates. The new parameterization significantly improved the model performance regarding simulation of observed daily N2O fluxes; r2 and RMSE improved from 0.11 and 198 g N2O-N ha−1 d−1 to 0.41 and 40 g N2O-N ha−1 d−1, respectively. Our analyses of the model results show that aggregates have a larger impact on the reduction than on the production of N2O. Reduction of N2O is more sensitive to changes in the drivers than production of N2O and is in that sense the key to understanding N2O emissions from denitrification. The effects of changing environmental conditions on reduction of N2O relative to N2O production strongly depend on the NO3 content of the soil. More anaerobic conditions have hardly any effect on the ratio of production to reduction if NO3 is abundant, but will decrease this ratio if NO3 is limiting. In the first case the emissions will increase, whereas in the second case the emissions will decrease. This study suggests that the current knowledge of the hydrological, biogeochemical and physical processes may be sufficient to understand the observed N2O fluxes from a fertilized clayey peatland. Further research is needed to test how aggregates affect the N2O fluxes from other soils or soils with different fertilization regimes.

We studied the effect of the deep-burrowing earthworm Lumbricus terrestris on the greenhouse gas (GHG) fluxes and global warming potential (GWP) of arable no-till soil using both field measurements and a controlled 15-week laboratory experiment. In the field, the emissions of nitrous oxide (N2O) and carbon dioxide (CO2) were on average 43 and 32 % higher in areas occupied by L. terrestris (the presence judged by the surface midden) than in adjacent, unoccupied areas (with no midden). The fluxes of methane (CH4) were variable and had no consistent difference between the midden and non-midden areas. Removing the midden did not affect soil N2O and CO2 emissions. The laboratory results were consistent with the field observations in that the emissions of N2O and CO2 were on average 27 and 13 % higher in mesocosms with than without L. terrestris. Higher emissions of N2O were most likely due to the higher content of mineral nitrogen and soil moisture under the middens, whereas L. terrestris respiration fully explained the observed increase in CO2 emissions in the laboratory. In the field, the significantly elevated macrofaunal densities in the vicinity of middens likely contributed to the higher emissions from areas occupied by L. terrestris. The activity of L. terrestris increased the GWP of field and laboratory soil by 50 and 18 %, but only 6 and 2 % of this increase was due to the enhanced N2O emission. Our results suggest that high N2O emissions commonly observed in no-till soils can partly be explained by the abundance of L. terrestris under no-till management and that L. terrestris can markedly regulate the climatic effects of different cultivation practises.

In this work the methane conversion factor (MCF) of untreated and anaerobically digested cattle manure (CM) as a function of storage temperature, time and co-digestion was measured in an in vitro experiment and modelled based on IPCC (2006) methodology (Tier 2). For this, one sample of untreated CM, one sample of mono-digested CM and three samples of CM co-digested with grass were incubated at seven different temperatures (from 5°C to 50°C) over 346 days. The main results showed that ultimate methane yield (B0) of CM is higher than the B0 reported by the IPCC (2006). Two temperature ranges should be considered for MCF evolution, below 15°C very low MCF was measured in this work for untreated CM, mono and co-digested samples. At higher temperatures, MCF obtained in this work and that provided by the IPCC could be comparable depending on storage time. Anaerobic mono-digestion decreased MCF compared to untreated CM at all temperatures and times, except in the temperature range between 20°C and 25°C if storage time is low, due to a lag phase observed in CM. This lag phase would probably not happen in real storage conditions depending on the proportion of old manure remaining in the storage tank. Co-digestion with grass-decreased MCF compared to mono-digestion, but increased CH4 production in terms of fresh matter due to the higher B0 of the mixture. Storage time, temperature and co-digestion should be considered in the quantification of CH4 emission from digested material.

To evaluate the effect of farming system on gaseous emission of N from soil, the measurements of nitrous oxide (N2O) were taken in organic and conventional paddy fields in tropics. Eleven soil samples from organic and neighboring conventional sites in Central Java, Indonesia were incubated at two different moisture contents expressed as water filled pores (WFPS), namely 75% WFPS and 100% WFPS. Emission of N2O-N at 75% WFPS was significantly higher in conventional management than in organic management. At 100% WFPS, the N2O-N emission was also higher in conventional than in organic farming system. Although it was not significantly different, it has significantly and positively correlations with SOC, total N and initial mineral N content. Due to the swelling ability of the high clay which is contained in soil samples, less N2O-N emission in 75% WFPS than in 100% WFPS was observed in the present study. The range of N2O-N emission at 75% WFPS was 0.01 – 0.03 kg N2O-N/ha in organic farming and 0.005 – 0.16 kg N2O-N/ha in conventional farming; for organic farming at 100% WFPS, the N2O-N emission was 0.04 – 61 kg N2O-N/ha and in conventional farming was 0.08 – 74 kg N2O-N/ha. This study concludes that organic farming in paddy fields might have more promising potential to mitigate N2O-N emission than conventional farming in paddy fields.

To date, technologies to recover ammonium from domestic wastewater from the mainstream have not found widespread application. This is largely due to the low ammonium concentrations in these wastewater streams. This paper reports on the use of polymer hydrogels for rapid sorption of ammonium from domestic wastewater coupled with efficient regeneration by mild acid washing. The sorption capacity of the hydrogel was 8.8–32.2 mg NH4–N/g, which corresponds to removal efficiencies ranging from 68% to 80% NH4–N, increasing proportionally with the initial ammonium concentration. It was, however, unaffected by changes in pH, as the sorption capacity remained constant from pH 5.0–8.0. Importantly, effective regeneration of the hydrogels under mildly acidic conditions (i.e. pH 4.0) was demonstrated with minimal loss in sorption performance following multiple sorption/desorption cycles. Overall, this study highlights the potential of low-cost polymer hydrogels for achieving mainstream ammonium recovery from domestic wastewater.

Dairy farms produce significant greenhouse gas (GHG) emissions and are therefore a focal point for GHG-mitigation practices. To develop viable mitigation options, we need robust (insensitive to changes in model parameters and assumptions) predictions of GHG emissions. To this end, we developed a stochastic model to estimate the robustness of predictions based on input parameters (GHG emission factors and production traits) and their uncertainties. In our study we explored how sensitive predictions of GHG emissions are to three factors: (1) system boundaries of the emission model (2) the uncertainty of input parameters due to quality of data or methodological choices (epistemic uncertainty) and (3) inherent variability in input parameters (variability uncertainty). To assess the effect of system boundaries, we compared two different boundaries: the “dairy farm gate” boundary (all GHG emissions are allocated to milk) and “system expansion” (the model gives a GHG credit to beef derived from culled cows and bull, heifer and calf fattening of surplus dairy calves outside the farm). Results using the farm-gate boundary provide guidance to dairy farmers to reduce GHG emissions of milk production. The results using system expansion are important for defining GHG abatement policies for milk and beef production. We found that the choice of system boundary had the strongest impact on the level and variation of predicted GHG emissions. Model predictions were least robust for lower-yielding dairy cow production systems and when we used system expansion. We also explored which GHG-abatement strategies have the most leverage by assessing the influence of each input parameter on model predictions. Predicted GHG emissions were least sensitive to variability-related uncertainty in production traits (i.e. replacement rate, calving interval). Lower-yielding production systems had the highest variation, indicating the highest potential for GHG mitigation of all production systems studied. Variation in predicted GHG emissions increased substantially when both epistemic and variability uncertainty in emission factors and variability uncertainty in production traits were included in the model. If the system boundary was set at the farm gate, the emission factor of N2O from nitrogen input into the soil had the highest impact on variation in predicted GHG emissions. This variation stems from uncertainties in predicting N2O emissions (epistemic uncertainty) but also from inherent variability of N2O emissions over time and space. The uncertainty of predicted GHG emissions can be reduced by increasing the precision in predicting N2O emissions. However, this additional information does not reduce GHG emissions itself. Knowing site specific variability of N2O emissions can help reduce GHG emissions by specific management (e.g. reduce soil compaction, adopted manure management, choice of suitable crops). In case of system expansion, uncertainty in GHG emission credit for dairy beef contributed the most to increasing the variation in predicted GHG emissions. The stochastic-model approach gave important insights into the robustness of model outcomes, which is crucial in the search for cost-effective GHG-abatement options. Despite the high degree of uncertainty when using system expansion, its results help identifying global GHG mitigation options of combined milk and beef production

Ruminant production contributes to emissions of nitrogen (N) to the environment, principally ammonia (NH3), nitrous oxide (N2O) and di-nitrogen (N2) to air, nitrate (NO3 -) to groundwater and particulate N to surface waters. Variation in dietary N intake will particularly affect excretion of urinary N, which is much more vulnerable to losses than is faecal N. Our objective is to review dietary effects on the level and form of N excreted in cattle urine, as well as its consequences for emissions of N2O. The quantity of N excreted in urine varies widely. Urinary N excretion, in particular that of urea N, is decreased upon reduction of dietary N intake or an increase in the supply of energy to the rumen microorganisms and to the host animal itself. Most of the N in urine (from 50% to well over 90%) is present in the form of urea. Other nitrogenous components include purine derivatives (PD), hippuric acid, creatine and creatinine. Excretion of PD is related to rumen microbial protein synthesis, and that of hippuric acid to dietary concentration of degradable phenolic acids. The N concentration of cattle urine ranges from 3 to 20 g/l. High-dietary mineral levels increase urine volume and lead to reduced urinary N concentration as well as reduced urea concentration in plasma and milk. In lactating dairy cattle, variation in urine volume affects the relationship between milk urea and urinary N excretion, which hampers the use of milk urea as an accurate indicator of urinary N excretion. Following its deposition in pastures or in animal houses, ubiquitous microorganisms in soil and waters transform urinary N components into ammonium (NH4 +), and thereafter into NO3 - and ultimately in N2 accompanied with the release of N2O. Urinary hippuric acid, creatine and creatinine decompose more slowly than urea. Hippuric acid may act as a natural inhibitor of N2O emissions, but inhibition conditions have not been defined properly yet. Environmental and soil conditions at the site of urine deposition or manure application strongly influence N2O release. Major dietary strategies to mitigating N2O emission from cattle operations include reducing dietary N content or increasing energy content, and increasing dietary mineral content to increase urine volume. For further reduction of N2O emission, an integrated animal nutrition and excreta management approach is required.

For the last 150 years many studies have shown the importance of earthworms for plant growth, but the exact mechanisms involved in the process are still poorly understood. Many important functions required for plant growth can be performed by soil microbes in the rhizosphere. To investigate earthworm influence on the rhizosphere microbial community, we performed a macrocosm experiment with and without Pontoscolex corethrurus (EW+ and EW−, respectively) and followed various soil and rhizosphere processes for 217 days with sugarcane. In EW+ treatments, N2O concentrations belowground (15 cm depth) and relative abundances of nitrous oxide genes (nosZ) were higher in bulk soil and rhizosphere, suggesting that soil microbes were able to consume earthworm-induced N2O. Shotgun sequencing (total DNA) revealed that around 70 microbial functions in bulk soil and rhizosphere differed between EW+ and EW− treatments. Overall, genes indicative of biosynthetic pathways and cell proliferation processes were enriched in EW+ treatments, suggesting a positive influence of worms. In EW+ rhizosphere, functions associated with plant-microbe symbiosis were enriched relative to EW− rhizosphere. Ecological networks inferred from the datasets revealed decreased niche diversification and increased keystone functions as an earthworm-derived effect. Plant biomass was improved in EW+ and worm population proliferated.

Emissions of nitrous oxide (N2O) from agricultural soils contribute to global warming and stratospheric ozone depletion. Applications of fertilizer nitrogen (N) increase N2O emission, but also increase agricultural production. Here, we report on the responses of crop yield, N2O emission and yield-scaled N2O emission (N2O emission per unit N uptake by grain and aboveground biomass) to different N fertilizer rates in a winter wheat–summer corn double-cropping system in the North China Plain. Soil N2O emission measurements were carried out for two years in a long-term field experiment, under semi-arid conditions with four flood irrigations events per year. Our results indicated that N2O emissions were linear functions and yield-scaled N2O emissions were cubic functions of N fertilizer application rate. Yield-scaled N2O emissions were lowest at application rates of 136 kg N ha−1 yr−1. Using a quadratic-plateau model, it was found that maximal crop yields were achieved at an application rate of 317 kg N ha−1 yr−1, which is 20% less than current practice. This level is suggested to be a compromise between achieving food security and mitigation N2O emissions.

The animal food chain contributes significantly to emission of greenhouse gases (GHGs). We explored studies that addressed options to mitigate GHG emissions in the animal production chain and concluded that most studies focused on production systems in developed countries and on a single GHG. They did not account for the complex interrelated effects on other GHGs or their relation with other aspects of sustainability, such as eutrophication, animal welfare, land use or food security. Current decisions on GHG mitigation in animal production, therefore, are hindered by the complexity and uncertainty of the combined effect of GHG mitigation options on climate change and their relation with other aspects of sustainability. There is an urgent need to integrate simulation models at animal, crop and farm level with a consequential life cycle sustainability assessment to gain insight into the multidimensional and sometimes conflicting consequences of GHG mitigation options. Highlights ¿ Most studies that address options to mitigate greenhouse gas (GHG) emissions in the animal production focus on systems in developed countries and on a single GHG. ¿ Current decisions on GHG mitigation in animal production are hindered by the complexity and uncertainty of the combined effect of GHG mitigation options on climate change and their relation with other aspects of sustainability. ¿ There is an urgent need to integrate simulation models at animal, crop and farm level with a consequential life cycle sustainability assessment to gain insight into the multidimensional and sometimes conflicting consequences of GHG mitigation options.

Nitrous oxide (N2O) emissions are highly variable in time, with high peak emissions lasting a few days to several weeks and low background emissions. This temporal variability is poorly understood which hampers the simulation of daily N2O emissions. In structured soils, like clay and peat, aggregates hamper the diffusion of oxygen, which leads to anaerobic microsites in the soil, favourable for denitrification. Diffusion of N2O out of the aggregates is also hampered, which leads to delayed emissions and increased reduction of N2O to N-2. In this model simulation study we investigate the effect of aggregates in soils on the N2O emissions. We present a parameterization to simulate the effects of aggregates on N2O production by denitrification and on N2O reduction. The parameterization is based on the mobile-immobile model concept. It was implemented in a field-scale hydrological-biogeochemical model combination. We compared the simulated fluxes with observed fluxes from a fertilized and drained peat soil under grass. The results of this study show that aggregates strongly affect the simulated N2O emissions: peak emissions are lower, whereas the background emissions are slightly higher. Including the effect of aggregates caused a 40% decrease in the simulated annual emissions relative to the simulations without accounting for the effects of aggregates. The new parameterization significantly improved the model performance regarding simulation of observed daily N2O fluxes; r(2) and RMSE improved from 0.11 and 198 g N2O-N ha(-1) d(-1) to 0.41 and 40 g N2O-N ha(-1) d(-1), respectively. Our analyses of the model results show that aggregates have a larger impact on the reduction than on the production of N2O. Reduction of N2O is more sensitive to changes in the drivers than production of N2O and is in that sense the key to understanding N2O emissions from denitrification. The effects of changing environmental conditions on reduction of N2O relative to N2O production strongly depend on the NO3 content of the soil. More anaerobic conditions have hardly any effect on the ratio of production to reduction if NO3 is abundant, but will decrease this ratio if NO3 is limiting. In the first case the emissions will increase, whereas in the second case the emissions will decrease. This study suggests that the current knowledge of the hydrological, biogeochemical and physical processes may be sufficient to understand the observed N2O fluxes from a fertilized clayey peatland. Further research is needed to test how aggregates affect the N2O fluxes from other soils or soils with different fertilization regimes.

Nitrous oxide (N2O) emission from agricultural land is an important component of the total annual greenhouse gas (GHG) budget. In addition, uncertainties associated with agricultural N2O emissions are large. The goals of this work were (i) to quantify the uncertainties of modelled N2O emissions caused by model input uncertainty at point and landscape scale (i.e. resolution), and (ii) to identify the main sources of input uncertainty at both scales. For the Dutch western fen meadow landscape, we performed a Monte Carlo uncertainty propagation analysis using the INITIATOR model. The Monte Carlo analysis used novel and state-of-the-art methods for estimating and simulating continuous-numerical and categorical input variables, handling spatial and cross-correlations and analyzing spatial aggregation effects. Spatial auto- and cross-correlation of uncertain numerical inputs that are spatially variable were represented by the linear model of coregionalization. Bayesian Maximum Entropy was used to quantify the uncertainty of spatially variable categorical model inputs. Stochastic sensitivity analysis was used to analyze the contribution of groups of uncertain inputs to the uncertainty of the N2O emission at point and landscape scale. The average N2O emission at landscape scale had a mean of 20.5 kg N2O-N ha(-1) yr(-1) and a standard deviation of 10.7 kg N2O-N ha(-1) yr(-1), producing a relative uncertainty of 52%. At point scale, the relative error was on average 78%, indicating that upscaling decreases uncertainty. Soil inputs and denitrification and nitrification inputs were the main sources of uncertainty in N2O emission at point scale. At landscape scale, uncertainty in soil inputs averaged out and uncertainty in denitrification and nitrification inputs was the dominant source of uncertainty. This was partly because these inputs were assumed constant across areas with the same soil type and land use, which is probably not very realistic. Experiments at landscape scale are needed to assess the spatial variability of these fractions and analyze how a more realistic representation influences the uncertainty budget at landscape scale. This research confirms that results from uncertainty analyses are often scale dependent and that results for one scale cannot directly be extrapolated to other scales. (C) 2010 Elsevier B.V. All rights reserved.

Annual terrestrial balances of methane (CH4) and nitrous oxide (N2O) are presented for a managed fen meadow in the Netherlands for 2006, 2007 and 2008, using eddy covariance (EC) flux measurements. Annual emissions derived from different methods are compared. The most accurate annual CH4 flux is achieved by gap filling EC fluxes with an empirical multivariate regression model, with soil temperature and mean wind velocity as driving variables. This model explains about 60% of the variability in observed daily CH4 fluxes. Annual N2O emissions can be separated into background emissions and event emissions due to fertilization. The background emission is estimated using a multivariate regression model also based on EC flux data, with soil temperature and mean wind velocity as driving variables. The event emissions are estimated using emission factors. The minimum direct emission factor is derived for six fertilization events by subtracting the background emission, and the IPCC default emission factor of 1% is used for the other events. In addition, the maximum direct emission factors are determined for the six events without subtracting the background emission. The average direct emission factor ranges from 1.2 to 2.8%, which is larger than the IPCC default value. Finally, the total terrestrial greenhouse gas balance is estimated at 16 Mg ha-1 year-1 in CO2-equivalents with contributions of 30, 25 and 45% by CO2, CH4 and N2O, respectively.

This paper focuses on improvements to livestock manure management to reduce environmental pollution and emission of greenhouse gases (GHG). Livestock manures contain large amounts of plant nutrients and organic matter (OM). Structural changes to livestock production and ample supply of cheap chemical fertilisers have decreased the interest and possibilities of farmers in using manure for the fertilisation of crops and grasslands and maintenance of soil fertility. As a result, many livestock producers dispose of manure as cheaply as possible causing serious pollution of soil, water and atmosphere. In addition, livestock production systems contribute to climate change by emission of the GHG carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O). Careful recycling of livestock manures to fertilise crops and grasslands and improve soil fertility is considered the most suitable and cost-effective option for environmentally friendly disposal. Manure management legislation in The Netherlands is described to explain the principles. These include complete collection of faeces and urine of confined livestock, adaptation of the period and rate of manure application to the N and P requirements of crops, and use of manure collection, storage and application techniques aiming at low ammonia (NH3) losses. Effects of sustainable manure management on GHG emissions are described. Optimising the period, rate and technique of manure application to crops and grassland causes effective utilisation of manure N and reduces direct and indirect losses of N2O. In addition, effective recycling of manure nutrients and OM allows a reduction in the use of chemical fertilisers and fossil energy and contributes to the maintenance or improvement of the carbon content of agricultural ecosystems. The relatively high costs of sustainable manure management stimulate farmers to optimise feed conversion and minimise manure production per unit of product by good livestock feeding and management practices. High feed conversion efficiency reduces CH4 emission by enteric fermentation and may reduce feed imports and related GHG emissions. In addition, it is shown that livestock categories differ widely in feed conversion efficiency and N and P excretion per unit of product. Finally, anaerobic digestion of livestock slurries provides a valuable energy source and reduces CH4 emission of stored slurry and, possibly, N2O emission after field application of the slurry.

The full greenhouse gas balance of nine contrasted grassland sites covering a major climatic gradient over Europe was measured during two complete years. The sites include a wide range of management regimes (rotational grazing, continuous grazing and mowing), the three main types of managed grasslands across Europe (sown, intensive permanent and semi-natural grassland) and contrasted nitrogen fertilizer supplies. At all sites, the net ecosystem exchange (NEE) of CO2 was assessed using the eddy covariance technique. N2O emissions were monitored using various techniques (GC-cuvette systems, automated chambers and tunable diode laser) and CH4 emissions resulting from enteric fermentation of the grazing cattle were measured in situ at four sites using the SF6 tracer method. Averaged over the two measurement years, net ecosystem exchange (NEE) results show that the nine grassland plots displayed a net sink for atmospheric CO2 of -240 +/- 70 g C m(-2) year(-1) (mean confidence interval at p > 0.95). Because of organic C exports (from cut and removed herbage) being usually greater than C imports (from manure spreading), the average C storage (net biome productivity, NBP) in the grassland plots was estimated at -104 +/- 73 g cm(-2) year(-1) that is 43% of the atmospheric CO2 sink. On average of the 2 years, the grassland plots displayed annual N2O and CH4 (from enteric fermentation by grazing cattle) emissions, in CO2-C equivalents, of 14 +/- 4.7 and 32 +/- 6.8 g CO2-C equiv. m(-2) year(-1), respectively. Hence, when expressed in CO2-C equivalents, emissions of N2O and CH4 resulted in a 19% offset of the NEE sink activity. An attributed GHG balance has been calculated by subtracting from the NBP: (i) N2O and CH4 emissions occurring within the grassland plot and (ii) off-site emissions of CO2 and CH4 as a result of the digestion and enteric fermentation by cattle of the cut herbage. On average of the nine sites, the attributed GHG balance was not significantly different from zero (-85 +/- 77 g CO2-C equiv. m(-2) year(-1)).

Measuring and mitigating methane (CH4) emissions from livestock is of increasing importance for the environment and for policy making. Potentially, the most sustainable way of reducing enteric CH4 emission from ruminants is through the estimation of genomic breeding values to facilitate genetic selection. There is potential for adopting genetic selection and in the future genomic selection, for reduced CH4 emissions from ruminants. From this review it has been observed that both CH4 emissions and production (g/day) are a heritable and repeatable trait. CH4 emissions are strongly related to feed intake both in the short term (minutes to several hours) and over the medium term (days). When measured over the medium term, CH4 yield (MY, g CH4/kg dry matter intake) is a heritable and repeatable trait albeit with less genetic variation than for CH4 emissions. CH4 emissions of individual animals are moderately repeatable across diets, and across feeding levels, when measured in respiration chambers. Repeatability is lower when short term measurements are used, possibly due to variation in time and amount of feed ingested prior to the measurement. However, while repeated measurements add value; it is preferable the measures be separated by at least 3 to 14 days. This temporal separation of measurements needs to be investigated further. Given the above issue can be resolved, short term (over minutes to hours) measurements of CH4 emissions show promise, especially on systems where animals are fed ad libitum and frequency of meals is high. However, we believe that for short-term measurements to be useful for genetic evaluation, a number (between 3 and 20) of measurements will be required over an extended period of time (weeks to months). There are opportunities for using short-term measurements in standardised feeding situations such as breath 'sniffers' attached to milking parlours or total mixed ration feeding bins, to measure CH4. Genomic selection has the potential to reduce both CH4 emissions and MY, but measurements on thousands of individuals will be required. This includes the need for combined resources across countries in an international effort, emphasising the need to acknowledge the impact of animal and production systems on measurement of the CH4 trait during design of experiments.

In many modelling studies on N cycling, denitrification is considered by a simplified process model. A widely used model describes denitrification as potential denitrification reduced by the soil conditions nitrate N content (N), degree of water saturation (S) and temperature (T). Henault and Germon, 2000 [Henault, C. and Germon, J.C., 2000. NEMIS, a predictive model of denitrification on the field scale. Eur. J. Soil Sci., 51: 257–270.] showed that this model worked satisfactorily for two data sets where parameters had been specifically derived for these data sets. This paper demonstrates that it may not always work well for other data, i.e., Dutch data sets. The model was parameterized for each of eight Dutch data sets, consisting of three sand, two heavy loam and three peat sites. After parameter optimisation the model is not able to predict individually measured actual denitrification rates. However, for sand and loam soils, but not for peat soils, the correspondence between measured and predicted average actual denitrification is good. This means that the calibrated model can predict, for those specific locations, cumulative denitrification rather well, provided that detailed information on soil conditions is available, either from measurements or from simulation models. The parameters and thus the reduction functions differed between the data sets. Parameter values within a class of soils, say sand, loam, and peat, were different. So care should be taken when using parameter values obtained from other studies. Albeit simple in its mathematical formulation, a widely used simplified denitrification process model needs to be parameterized for each location. The parameter optimisation is likely to be influenced by errors in the data. Therefore, an analysis on the effect of errors is presented based on an artificial data set. This data set was constructed consisting of 100 realisations of the soil conditions N, S and T, each drawn from a (log-)normal distribution based on the mineral Dutch data sets. For each realisation the relative denitrification rate (Dr) was computed based on a ‘true’ set of parameters. Next, measurement errors were introduced on Dr, N, S and T, either from a uniform or a normal distribution. For each of the 100 data sets the data were perturbed 100 times with newly drawn measurement errors. The perturbed data sets (10,000) were then optimised by the model. The coefficients of variation belonging to the estimates were large. This exercise can only be used to demonstrate possible directions of effects from errors, but it cannot be used to fully judge results obtained from real data sets.

Agriculture contributes significantly to the anthropogenic emissions of non-CO2 greenhouse gases methane and nitrous oxide. In this paper, a review is presented of the agriculture related sources of methane and nitrous oxide, and of the main strategies for mitigation. The rumen is the most important source of methane production, especially in cattle husbandry. Less, but still substantial, amounts of methane are produced from cattle manures. In pig and poultry husbandry, most methane originates from manures. The main sources of nitrous oxide are: nitrogen fertilisers, land applied animal manure, and urine deposited by grazing animals. Most effective mitigation strategies for methane comprise a source approach, i.e. changing animals’ diets towards greater efficiencies. Methane emissions, however, can also be effectively reduced by optimal use of the gas produced from manures, e.g. for energy production. Frequent and complete manure removal from animal housing, combined with on-farm biogas production is an example of an integratedon-farm solution. Reduced fertiliser nitrogen input, optimal fertiliser form,adding nitrification inhibitors,landdrainage management, andreduced landcompaction byrestricted grazing arethebestways to mitigate nitrous oxide emissions from farm land, whereas, management of bedding material and solid manure reduce nitrous oxide emissions from housing and storage. Other than for methane, mitigation measures for nitrous oxide interact with other important environmental issues, like reduction of nitrate leaching and ammonia emission. Mitigation strategies for reduction of the greenhouse gases should also minimize pollution swapping. # 2005 Elsevier B.V. All rights reserved.

Urine patches in pastures rank among the highest sources of the greenhouse gas nitrous oxide (N2O) from animal production systems. Previous laboratory studies indicate that N2O emissions for urine-N in pastures may increase with a factor five or eight in combination with soil compaction and dung, respectively. These combinations of urine, compaction and dung occur regularly in pastures, especially in so-called camping areas. The aims of this study were (i) to experimentally quantify the effect of compaction and dung on emission factors of N2O from urine patches under field conditions; (ii) to detect any seasonal changes in emission from urine patches; and (iii) to quantify possible effects of urine concentration and -volume. A series of experiments on the effects of compaction, dung, urine-N concentration and urine volume was set up at a pasture on a sandy soil (typic Endoaquoll) in Wageningen, the Netherlands. Artificial urine was applied 8 times in the period August 2000–November 2001, and N2O emissions were monitored for a minimum of 1 month after each application. The average emission factor for urine-only treatments was 1.55%. Over the whole period, only soil compaction had a clear significant effect, raising the average N2O emissions from urine patches from 1.30% to 2.92% of the applied N. Dung had no consistent effect; although it increased the average emissions from 1.60% to 2.82%, this was clearly significant (P 50%, avoiding camping areas in pastures, and on avoiding grazing under moist soil conditions. Greenhouse gas budgets for grazing conditions should include the effects of soil compaction and dung to represent actual emissions.

Studies on emissions of nitrous oxide (N2O) from agricultural soils mostly focus on fluxes between the soil and the atmosphere or are limited to the atmosphere in the topsoil. However, in soils with shallow water tables, significant N2O formation may occur closer to the groundwater. The aims of this study were (i) to determine the importance of subsoil N2O formation in a sandy soil; and (ii) to obtain a quantitative insight in the contribution of subsoil N2O to the overall losses of N2O to the environment. We applied 15N labeled fertilizer at a rate of 5.22 kg 15N ha−1; 50% as Ca(NO3)2 and 50% as NH4Cl, on a mesic typic Haplaquod seeded with potatoes (Solanum tuberosum L.), and traced soil N2O concentrations and fluxes over a one-year period. Throughout the year, total N2O and the amount of 15N recovered in soil N2O were highest in the subsoil, with a maximum concentration at 48 cm depth in mid-February of 19900 μl m−3 and 24 μg 15N m−3, respectively. The maximum concentration coincided with the highest water-filled pore space of 71%. The cumulative flux of N2O was 446 g N2O-N ha−1, the recovery of 15N in this flux was 0.06%. During the summer, maximum fluxes followed high soil N2O concentrations. During winter, no such relation was found. We concluded that the formation of N2O was the highest in the subsoil, largely controlled by water-filled pore space rather than NO 3 − concentration or temperature. Although high subsoil N2O concentrations did not lead to high surface fluxes of N2O in the winter, artificial draining may lead to high indirect N2O emissions through supersaturated drainage water.Studies on emissions of nitrous oxide (N2O) from agricultural soils mostly focus on fluxes between the soil and the atmosphere or are limited to the atmosphere in the topsoil. However, in soils with shallow water tables, significant N2O formation may occur closer to the groundwater. The aims of this study were (i) to determine the importance of subsoil N2O formation in a sandy soil; and (ii) to obtain a quantitative insight in the contribution of subsoil N2O to the overall losses of N2O to the environment. We applied N-15 labeled fertilizer at a rate of 5.22 kg N-15 ha(-1); 50% as Ca(NO3)(2) and 50% as NH4Cl, on a mesic typic Haplaquod seeded with potatoes (Solanum tuberosum L.), and traced soil N2O concentrations and fluxes over a one-year period. Throughout the year, total N2O and the amount of N-15 recovered in soil N2O were highest in the subsoil, with a maximum concentration at 48 cm depth in mid-February of 19900 mu l m(-3) and 24 mu g N-15 m(-3), respectively. The maximum concentration coincided with the highest water-filled pore space of 71%. The cumulative flux of N2O was 446 g N2O-N ha(-1), the recovery of N-15 in this flux was 0.06%. During the summer, maximum fluxes followed high soil N2O concentrations. During winter, no such relation was found. We concluded that the formation of N2O was the highest in the subsoil, largely controlled by water-filled pore space rather than NO3- concentration or temperature. Although high subsoil N2O concentrations did not lead to high surface fluxes of N2O in the winter, artificial draining may lead to high indirect N2O emissions through supersaturated drainage water.

Agriculture contributes to global warming through emissions of nitrous oxide, and methane, and to acidification mainly through emissions of ammonia. Measures to reduce one of these gases may affect emissions of others. Policies neglecting these interrelations may be sub_optimal. This study investigated interrelations between abatement of ammonia, nitrous oxide, and methane from European agriculture. We first studied how emission reduction technologies simultaneously affect the emissions of these three gases. Next, we analyzed for the Netherlands how the costs of emission reduction are affected when these interrelations are included in the analysis. Cost_effectiveness analysis of emission reductions in agriculture in the Netherlands indicates that increased nitrous oxide emissions due to ammonia abatement can be avoided at low cost. Finally we calculated at the European level the side_effects on ammonia emissions and the greenhouse gases nitrous oxide and methane of various emissions scenarios for European agriculture. We estimated that nitrous oxide emissions from European agriculture may increase as a side_effect of ammonia abatement, whereas ammonia emissions may decrease due to nitrous oxide and methane mitigation. The conclusion is that simultaneous reductions in emissions can be realized at lower overall costs using an integrated approach.

Dairy farms produce significant greenhouse gas (GHG) emissions and are therefore a focal point for GHG-mitigation practices. To develop viable mitigation options, we need robust (insensitive to changes in model parameters and assumptions) predictions of GHG emissions. To this end, we developed a stochastic model to estimate the robustness of predictions based on input parameters (GHG emission factors and production traits) and their uncertainties. In our study we explored how sensitive predictions of GHG emissions are to three factors: (1) system boundaries of the emission model (2) the uncertainty of input parameters due to quality of data or methodological choices (epistemic uncertainty) and (3) inherent variability in input parameters (variability uncertainty). To assess the effect of system boundaries, we compared two different boundaries: the “dairy farm gate” boundary (all GHG emissions are allocated to milk) and “system expansion” (the model gives a GHG credit to beef derived from culled cows and bull, heifer and calf fattening of surplus dairy calves outside the farm). Results using the farm-gate boundary provide guidance to dairy farmers to reduce GHG emissions of milk production. The results using system expansion are important for defining GHG abatement policies for milk and beef production. We found that the choice of system boundary had the strongest impact on the level and variation of predicted GHG emissions. Model predictions were least robust for lower-yielding dairy cow production systems and when we used system expansion. We also explored which GHG-abatement strategies have the most leverage by assessing the influence of each input parameter on model predictions. Predicted GHG emissions were least sensitive to variability-related uncertainty in production traits (i.e. replacement rate, calving interval). Lower-yielding production systems had the highest variation, indicating the highest potential for GHG mitigation of all production systems studied. Variation in predicted GHG emissions increased substantially when both epistemic and variability uncertainty in emission factors and variability uncertainty in production traits were included in the model. If the system boundary was set at the farm gate, the emission factor of N2O from nitrogen input into the soil had the highest impact on variation in predicted GHG emissions. This variation stems from uncertainties in predicting N2O emissions (epistemic uncertainty) but also from inherent variability of N2O emissions over time and space. The uncertainty of predicted GHG emissions can be reduced by increasing the precision in predicting N2O emissions. However, this additional information does not reduce GHG emissions itself. Knowing site specific variability of N2O emissions can help reduce GHG emissions by specific management (e.g. reduce soil compaction, adopted manure management, choice of suitable crops). In case of system expansion, uncertainty in GHG emission credit for dairy beef contributed the most to increasing the variation in predicted GHG emissions. The stochastic-model approach gave important insights into the robustness of model outcomes, which is crucial in the search for cost-effective GHG-abatement options. Despite the high degree of uncertainty when using system expansion, its results help identifying global GHG mitigation options of combined milk and beef production

As energy crop production on European croplands expands, driven by accelerating consumption of bioenergy, there is a pressing need to evaluate the environmental impacts associated with this production. The present study considers on-going yield increases as a means of boosting agricultural output which results in a limited need to convert nature areas and grasslands to additional cropland. For nine land-use variants, the study evaluates cumulative greenhouse gas emissions, net organic carbon fluxes from the soil, and abated emissions achieved by replacing fossil fuels for transport with biofuels. The main finding is that, in European agriculture, it is possible to combine large-scale biomass production with food production sustained at current levels, with limited direct or indirect land-use changes and while accomplishing significant net greenhouse gas mitigation. Maintaining the current (business as usual) agricultural system results in 4.9 GtCO2-eq. of cumulative emissions by 2030. Intensifi ed food production and energy crop production on freed cropland combined with mitigation measure implementation signifi cantly reduces cumulative emissions for the annual crop groups of oil, starch and sugarbeet to 1.9, 1.5 and 2.1 GtCO2-eq., respectively. By 2030, perennial energy crop production can mitigate cumulative emissions to a large extent, reaching negative emissions (i.e. net sequestration) for grass and wood crops of –3.3 and –4.5 GtCO2-eq., respectively. For the variants compared to the baseline, nitrous oxide emissions will increase modestly due to higher fertilizer-application rates, though at improved effi ciencies per unit crop quantity produced. Emission mitigation results partly from the temporary increase in SOC sequestration though mainly from replacement of fossil resources by biomass resources. The results indicate that research and policy efforts aimed at further increasing productivity can raise the output from existing European croplands while being able to reduce or mitigate emissions significantly.